Coding With David

  APIs Are More Than REST: A Practical Guide to How Software Really Talks Think for a moment about your daily digital life: You pay for coffee with your phone You check your bank balance Your smartwatch records your steps Your software talks to other software All of it works—even though none of these systems were built by the same team How? APIs. But if your first thought is “REST API, JSON, HTTP GET/POST” —you’re only seeing a small slice of the picture. APIs come in many shapes, sizes, and communication patterns. And understanding that broader landscape is one of the most valuable architectural skills we can build today. Today, let’s zoom out. 🚀 What Is an API, Really? API stands for Application Programming Interface , but that technical name hides the real purpose: An API is a contract that lets two pieces of software communicate without needing to know how each other works. It’s about clarity. About abstraction. About independence. APIs let softwa...

  Why DotEnv is PERFECT for both regular apps and the new .NET 10 file-based apps If you're building modern .NET applications—especially those new single-file .NET 10 apps —you need a configuration approach that’s simple, portable, secure-ish, and doesn’t require a full appsettings.json pipeline just to load two key-value pairs. Guess what? The DotEnv NuGet package is the hero we've been waiting for . 🎉 DotEnv brings the simplicity of JavaScript, Python, and Linux environments straight into .NET—no ceremony, no boilerplate, just clean environment variables in a .env file that you load with one line of code. Today, I'm going to show you why DotEnv is a game changer and why it's one of the BEST configuration choices for both full .NET applications and the new file-based apps introduced in .NET 10. 🚀 Why DotEnv? Because configuration shouldn’t hurt your brain. ✔ Perfect for simple apps Your console app doesn't need a full JSON hierarchy the size of a Tolkein nov...

In .NET 10, Microsoft introduced one of the most exciting quality-of-life features C# has seen in years: file-based apps . If you’ve ever wished C# development felt more like Python—instant scripts, no boilerplate, no projects—this new model was built for you. File-based apps let you write a single .cs file, run it immediately with dotnet run , and skip the ceremony of projects, folders, .csproj files, and startup templates. It’s C#, but with a scripting-first mindset. In this article, we’ll break down: What file-based apps are Why Microsoft built them How they help onboard developers faster How they compete with Python-style scripting workflows How to use packages, properties, and project metadata Limitations of file-based apps How to make them executable on macOS and Linux Step-by-step setup and examples What Are File-Based Apps? File-based apps are standalone C# programs written entirely in a single file , without needing: A csproj A project folder s...

  In modern development, we rely heavily on AI to assist with coding, debugging, and architectural decisions. But every once in a while, a problem comes along that AI can’t quite crack—at least not without a developer who understands the underlying language and can think beyond AI’s suggestions. Recently, I ran into exactly that scenario while working with an application that uses Excel spreadsheets as a data source. Yes, it’s not ideal. No, that part isn’t changing. The real issue was something far more painful: The spreadsheet columns kept changing positions. Every time a new spreadsheet arrived, the columns shifted around unpredictably. This caused the parser to misalign fields, break imports, and generally ruin my day. What We Tried (with AI’s Help) I paired with AI to generate a variety of solutions: Custom Excel parser using NuGet packages CSV parser variants Multiple fallback strategies Different libraries for column mapping and validation These solution...

  Hands-on impressions using a Snapdragon X Elite laptop Local LLMs have exploded in popularity, and with new hardware like the Snapdragon X Elite , it’s finally practical to run powerful AI models entirely on your machine—fast, private, offline, and inexpensive. In this guide, I’ll walk you through three of the most popular tools for running local models: Ollama LM Studio Microsoft Foundry For each, I’ll cover: How to install it Minimum hardware requirements Rough model availability Pros and cons My personal performance testing results All tests were done on: 🧑‍💻 My Test Hardware Microsoft Surface Laptop, 7th Edition Component Details CPU Snapdragon X Elite (X1E80100), 12 cores @ 3.40 GHz RAM 32 GB OS Windows 11 Home, Build 26200 GPU / AI Acceleration DirectX 12 / NPU support Notes ARM-based architecture This hardware is extremely efficient for local inference—especially for optimized models. 1. Ollama ✔️ “The easiest way to run local LLM...